ELECTRICAL ENERGY SUPPLIES SAFETY VERSUS BUSINESS MODELS OF POWER COMPANIES IN POLAND

被引:0
|
作者
Brzoska, Jan [1 ]
机构
[1] Silesian Tech Univ, Fac Org & Management, Gliwice, Poland
关键词
Power safety; power companies; business model;
D O I
暂无
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Provision of power safety is one (next to growth of competitiveness and power efficiency of economy and reduction of power industry impact on the environment) of the main goals and priorities of Polish power policy until 2050. It level depends on many factors among which electrical energy supplies safety is very important. To high extent, it does and will depend on business models of power companies operating on even more competitive energy market. Electrical energy supplies safety is found to be one of value components created by power company business model. Purpose of the paper was the evaluation of business models in the aspect of their ability to contribute to power safety. Subject of the research is structures of power companies' business models and the results they attain, in particular related to electrical energy supplies safety. It also shows the directions of strategic operations for its improvement. The research was performed in four Polish power corporations owing over 90% of share in the electrical energy supplies in Poland.
引用
收藏
页码:244 / 249
页数:6
相关论文
共 33 条
  • [21] First international workshop on electrical power and energy systems safety, security and Resilience (EPESec 2020)
    Sarigiannidis, Panagiotis
    Gkioulos, Vasileios
    Kolokotronis, Nicholas
    Rokkas, Theodoros
    Kavallieros, Dimitris
    [J]. 2020, Association for Computing Machinery
  • [22] Startups versus incumbents in 'green' industry transformations: A comparative study of business model archetypes in the electrical power sector
    Palmie, Maximilian
    Boehm, Jonas
    Friedrich, Jonas
    Parida, Vinit
    Wincent, Joakim
    Kahlert, Jonas
    Gassmann, Oliver
    Sjodin, David
    [J]. INDUSTRIAL MARKETING MANAGEMENT, 2021, 96 : 35 - 49
  • [23] Social Virtual Energy Networks: Exploring Innovative Business Models of Prosumer Aggregation with Virtual Power Plants
    Wainstein, Martin E.
    Dargaville, Roger
    Bumpus, Adam
    [J]. 2017 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2017,
  • [24] Optimal cycling time trial position models: Aerodynamics versus power output and metabolic energy
    Fintelman, D. M.
    Sterling, M.
    Hemida, H.
    Li, F. -X.
    [J]. JOURNAL OF BIOMECHANICS, 2014, 47 (08) : 1894 - 1898
  • [25] Construction of continuous simulation models of pulse converters of spacecraft electrical power systems with hydrogen energy storage
    Torgaeva, D. S.
    Kabirov, V. A.
    Semenov, V. D.
    Akhtyrskiy, K. A.
    Otto, A. I.
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2023, 48 (49) : 18918 - 18929
  • [26] Guest Editorial for the Special Section on Advances in Renewable Energy Forecasting: Predictability, Business Models and Applications in the Power Industry
    Bessa, Ricardo J.
    Pinson, Pierre
    Kariniotakis, George
    Srinivasan, Dipti
    Smith, Charlie
    Amjady, Nima
    Zareipour, Hamidreza
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2022, 13 (02) : 1166 - 1168
  • [27] Considering environmental impacts of energy storage technologies: A life cycle assessment of power-to-gas business models
    Tschiggerl, Karin
    Sledz, Christian
    Topic, Milan
    [J]. ENERGY, 2018, 160 : 1091 - 1100
  • [28] Stochastic versus Fuzzy Models-A Discussion Centered on the Reliability of an Electrical Power Supply System in a Large European Hospital
    Pinto, Constancio Antonio
    Farinha, Jose Torres
    Raposo, Hugo
    Galar, Diego
    [J]. ENERGIES, 2022, 15 (03)
  • [29] Water-energy-food nexus and business excellence models for a sustainability maturity evaluation of ten agri-food companies from Brazil and Kenya
    Caixeta, Fernando
    Saraiva, Pedro
    Freire, Fausto
    Shitandi, Anakalo
    [J]. JOURNAL OF CLEANER PRODUCTION, 2023, 420
  • [30] Enhancing Electrical Power Demand Prediction Using LSTM-Based Deep Learning Models for Local Energy Communities
    Pushpavalli, M.
    Dhanya, D.
    Kulkarni, Megha
    Rajitha Jasmine, R.
    Umarani, B.
    Ramprasadreddy, M.
    Garapati, Durga Prasad
    Yadav, Ajay Singh
    Rajaram, A.
    [J]. ELECTRIC POWER COMPONENTS AND SYSTEMS, 2024,